#!/usr/bin/env python
# coding: utf-8

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import pandas as pd
import matplotlib.pyplot as plt
import matplotlib as mpl
import seaborn as sns

import highlight_text


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# the famous import font code to use Andale Mono
import matplotlib.font_manager
from IPython.core.display import HTML

def make_html(fontname):
    return "<p>{font}: <span style='font-family:{font}; font-size: 24px;'>{font}</p>".format(font=fontname)

code = "\n".join([make_html(font) for font in sorted(set([f.name for f in matplotlib.font_manager.fontManager.ttflist]))])


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#import data
df = pd.read_csv('beeswarmTutorial.csv')


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#set default colors
text_color = 'white'
background = '#313332'


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#look at top of dataframe
df.head()


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#create a new column for progressive passes per 90
df['per90'] = df['Prog']/df['90s']
df


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#filter the dataframe so it is only players who have played more than 6.5 90's which is about 585 minutes
df = df[df['90s']>=6.5].reset_index()
df


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df.describe()


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df = df.sort_values(by='per90',ascending=False)


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df = df[df['Pos'] != 'GK']


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df.head(10)


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fig, ax = plt.subplots(figsize=(10,5))
fig.set_facecolor(background)
ax.patch.set_facecolor(background)

#set up our base layer
mpl.rcParams['xtick.color'] = text_color
mpl.rcParams['ytick.color'] = text_color

ax.grid(ls='dotted',lw=.5,color='lightgrey',axis='y',zorder=1)
spines = ['top','bottom','left','right']
for x in spines:
    if x in spines:
        ax.spines[x].set_visible(False)

sns.swarmplot(x='per90',data=df,color='white',zorder=1)

#plot thiago
plt.scatter(x=9.87,y=0,c='red',edgecolor='white',s=200,zorder=2)
plt.text(s='Thiago',x=9.87,y=-.04,c=text_color)

#plot de bruyne
plt.scatter(x=7.564,y=0,c='blue',edgecolor='white',s=200,zorder=2)

plt.title('Progressive Passes in the Premier League 2020/21',c=text_color,fontsize=14)

plt.xlabel('Progressive Passes per 90',c=text_color)



#plt.savefig('swarm.png',dpi=500,bbox_inches = 'tight',facecolor=background)


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#import our next dataframe
df2 = pd.read_csv('beeswarm2.csv')


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df2.head(10)


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#do some data preprocessing and cleaning

#split the player names
df2['Player'] = df2['Player'].str.split('\\',expand=True)[0]

df2 = df2[df2['Pos'] != 'GK']

df2 = df2[df2['90s'] > 6.5].reset_index()


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#make the per 90 stats
#metrics = ['Prog90','1/390','xA90','Cmp%','KP90','PPA90']
df2['Prog'] = df2['Prog'] / df2['90s']
df2['1/3'] = df2['1/3'] / df2['90s']
df2['xA'] = df2['xA'] / df2['90s']
df2['KP'] = df2['KP'] / df2['90s']
df2['PPA'] = df2['PPA'] / df2['90s']


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print(df2.head())

df2.Player.unique()


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#create a list of 6 metrics to compare
metrics = ['Prog','1/3','xA','Cmp%','KP','PPA']


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fig,axes = plt.subplots(3,2,figsize=(14,10))
fig.set_facecolor(background)
ax.patch.set_facecolor(background)

#set up our base layer
mpl.rcParams['xtick.color'] = text_color
mpl.rcParams['ytick.color'] = text_color

#create a list of comparisons
counter=0
counter2=0
met_counter = 0

for i,ax in zip(df2['Player'],axes.flatten()):
    ax.set_facecolor(background)
    ax.grid(ls='dotted',lw=.5,color='lightgrey',axis='y',zorder=1)
    
    spines = ['top','bottom','left','right']
    for x in spines:
        if x in spines:
            ax.spines[x].set_visible(False)
            
    sns.swarmplot(x=metrics[met_counter],data=df2,ax=axes[counter,counter2],zorder=1,color='#64645e')
    ax.set_xlabel(f'{metrics[met_counter]}',c='white')
    
    for x in range(len(df2['Player'])):
        #if df2['Player'][x] == 'Thiago Alcántara':
            #ax.scatter(x=df2[metrics[met_counter]][x],y=0,s=200,c='red',zorder=2)
        if df2['Player'][x] == 'İlkay Gündoğan':
            ax.scatter(x=df2[metrics[met_counter]][x],y=0,s=200,c='#6CABDD',zorder=2)
                        
    met_counter+=1
    if counter2 == 0:
        counter2 = 1
        continue
    if counter2 == 1:
        counter2 = 0
        counter+=1
        

        
s='<Ilkay Gündogan> Premier League Passing Stats'
highlight_text.fig_text(s=s,
                x=.25, y=.88,
                #highlight_weights = ['bold'],
                fontsize=22,
                fontfamily = 'Andale Mono',
                color = text_color,
                highlight_colors = ['#6CABDD'],
                va='center'
               )

fig.text(.12,.05,"all stats per 90 / Goal Keepers and those with less than 6.5 90's played excluded",fontsize=11, fontfamily='Andale Mono',color=text_color)
fig.text(.12,.03,"@mckayjohns / data via fbref.com + Statsbomb", fontstyle='italic',fontsize=11, fontfamily='Andale Mono',color=text_color)

plt.savefig('test.png',dpi=500,bbox_inches = 'tight',facecolor=background)


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